code: def train_one_epoch(self, current_epoch):
      num_iters = 0
      with tqdm.tqdm(total=self.total_iter_per_epoch) as bar:
          while num_iters < self.total_iter_per_epoch:
              for data_batch in self.data.get_train_batches():
                  loss = self.algorithm.train_one_iter(
                      data_batch, current_epoch
                  )
                  num_iters += 1
                  bar.update(1)
  
                  if num_iters >= self.total_iter_per_epoch:
                      break
  
file_path: PARL/benchmark/torch/maml++/maml_agent.py
imports: import numpy
  import scipy
  import parl
  import tqdm
label_desc: Use image node_id 2 for calling the MAMLAgent obj's underlying member method code with example usage: obj.train_one_epoch(current_epoch) without return types